Sociodemographic Factors Influencing the Uptake of Rapid Diagnostic Test Kits for the Management of Malaria among Mothers of Under Five in a Typical Nigerian Population
Notice bibliographique
Résumé
Introduction : Globally, malaria constitutes a crucial public health challenge since it is the third major cause of death among children under the age of 5. Prompt and effectual malaria diagnosis is the major approach to the control and management of the disease. Objectives : The study investigated sociodemographic factors that influence the uptake of rapid diagnostic test (RDT) for malaria management among mothers of under 5. Method of Study: A descriptive cross-sectional design was used in the study in which 420 mothers of under 5 were randomly selected from five electoral wards in Owerri West L.G.A of Imo state. Structured questionnaire was used in data collection. Data were analyzed with SPSS statistical package (Version 21) in which Chi-square at 5% probability level was used to ascertain the association between sociodemographic and uptake of rapid diagnostic test (RDT). Results : Results showed that the mothers 161 (38%) were mostly in 30–49 years age bracket, were married (%). More than one-quarter of them was secondary school certificate holders who were civil servants who earn average monthly income of 10,000–17,000₦ 183 (44%). Less than half 180 (42.9%) of the mothers do test their child with RDT, particularly when their child has fever 103 (24.5%). Moreover, larger proportions 161 (89%) of this group know how to carry out RDT. Most of them indicated positive result of RDT to be double line on the strip 155 (86.1%). More than three-quarter of them 168 (93.3%) still use RDT even when they are aware that it involved finger prick of blood from the child. Majority of them 252 (60%) indicated that their custom/religion allows blood test when the child is ill. It was shown that the uptake of mRDT was more pronounced among mothers within the age group of 18–29 years (67.5%) (χ2 = 50.12; P < 0.001) who were single (75%) ( χ 2 = 74.77; P < 0.001). Uptake of mRDT was also highest (71.4%) among respondents who had tertiary education ( χ 2 = 91.35, P < 0.001) and are civil servants (57.1%) ( χ 2 = 65.80; P < 0.001) who earn average monthly income of 18,000 (68.8%) ( χ 2 = 34.65; P < 0.001). Within the communities, uptake of mRDT was highest among mothers from Obinze compared to other communities with significant association ( χ 2 = 22.17; P < 0.001). Conclusion : Uptake will, however, be enhanced if the cost of RDT-based management is reduced. Enhancing the health education through media, conferences, seminars, and workshops using local dialects will also help in raising the knowledge and understanding of less or non-educated mothers on the benefits of RDT. Keywords: Malaria, Management, rapid diagnostic test, sociodemographic factors, uptake
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».